Instructions to use AmirMohseni/BERT-Router-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmirMohseni/BERT-Router-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AmirMohseni/BERT-Router-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AmirMohseni/BERT-Router-base") model = AutoModelForSequenceClassification.from_pretrained("AmirMohseni/BERT-Router-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c256810c81af7868330a51210206d6bc2ab6d21aa915c16c873f7ef588e9a370
- Size of remote file:
- 438 MB
- SHA256:
- d023842219d2ecda3110ad20430e0d1677393eafc30069d7f1cd82e0cb9c9b23
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